/qgis-plugin-deepness

Deepness is a remote sensing plugin that enables deep learning inference in QGIS

Primary LanguagePythonApache License 2.0Apache-2.0

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Deepness: Deep Neural Remote Sensing QGIS Plugin

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Plugin for QGIS to perform map/image segmentation, regression and object detection with (ONNX) neural network models.

Introduction video

Video title

Documentation

You can find the documentation here.

Deepness Model ZOO

Check our example models in the Model ZOO.

Development

  • Install QGIS (the plugin was tested with QGIS 3.12)
    • Debian/Ubuntu based systems: sudo apt install qgis
    • Fedora: sudo dnf install qgis-devel
    • Arch Linux: sudo pacman -S qgis
    • Windows, macOS and others
  • Create virtual environment (with global packages inherited!):
python3 -m venv venv --system-site-packages
  • Create a symlink to our plugin in a QGIS plugin directory:
ln -s $PROJECT_DIR/src/deepness ~/.local/share/QGIS/QGIS3/profiles/default/python/plugins/deepness
  • Activate the environment and install requirements:
. venv/bin/activate
pip install -r requirements.txt
  • Run QGis in the virtual environment:
export IS_DEBUG=true  # to enable some debugging options
qgis
  • Enable Deepness plugin in the Plugins -> Manage and install plugins
  • Install and enable:
    • Plugin reloader plugin - allows plugins reloading
    • first aid plugin - prints stack traces for exceptions

After the plugin code is modified, use the Plugin reloader to reload our plugin.

Unit tests

See test/README.md

Bugs, feature requests and questions

If you encountered some problems or have some feature requests you think will make this project better, consider opening an issue.

If you don't understand something and/or have some questions, ask them in Discussions.

Contributing

PRs are welcome! Read our General Information for Developers. Consider discussing your plans with maintainers.

Citation

Is our plugin help you in research? Please cite it:

@article{ASZKOWSKI2023101495,
title = {Deepness: Deep neural remote sensing plugin for QGIS},
journal = {SoftwareX},
volume = {23},
pages = {101495},
year = {2023},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2023.101495},
url = {https://www.sciencedirect.com/science/article/pii/S2352711023001917},
author = {Przemysław Aszkowski and Bartosz Ptak and Marek Kraft and Dominik Pieczyński and Paweł Drapikowski},
keywords = {QGIS, Deep learning, Remote sensing, Segmentation, Object detection},
}